Package: naspaclust Type: Package Title: Nature-Inspired Spatial Clustering Version: 0.2.2 Authors@R: c(person(given = "Bahrul Ilmi", family = "Nasution", role = c("aut", "cre"), email = c("bahrulnst@gmail.com","14.8034@stis.ac.id")), person(given = "Robert", family = "Kurniawan", role = "aut", email = "robertk@stis.ac.id"), person(given = "Rezzy Eko", family = "Caraka", role = "aut", email = "rezzyekocaraka@gmail.com")) Suggests: ppclust, cluster, ggplot2 Imports: Rdpack, rdist, stabledist, beepr RdMacros: Rdpack Author: Bahrul Ilmi Nasution [aut, cre], Robert Kurniawan [aut], Rezzy Eko Caraka [aut] Maintainer: Bahrul Ilmi Nasution Description: Implement and enhance the performance of spatial fuzzy clustering using Fuzzy Geographically Weighted Clustering with various optimization algorithms, mainly from Xin She Yang (2014) with book entitled Nature-Inspired Optimization Algorithms. The optimization algorithm is useful to tackle the disadvantages of clustering inconsistency when using the traditional approach. The distance measurements option is also provided in order to increase the quality of clustering results. The Fuzzy Geographically Weighted Clustering with nature inspired optimisation algorithm was firstly developed by Arie Wahyu Wijayanto and Ayu Purwarianti (2014) using Artificial Bee Colony algorithm. License: GPL-3 Encoding: UTF-8 LazyData: true RoxygenNote: 7.1.1 Repository: https://bmlmcmc.r-universe.dev Date/Publication: 2025-06-03 12:33:05 UTC RemoteUrl: https://github.com/bmlmcmc/naspaclust RemoteRef: HEAD RemoteSha: 4c81348c8372541e67f2cfe2bae70e30defbf10e NeedsCompilation: no Packaged: 2026-06-16 11:50:00 UTC; root Depends: R (>= 3.5.0)